基于半经验模型驱动协同仿真下集成式固体氧化物燃料电池冷热电联供系统的多目标优化与后验多准则决策

Abstract An integrative solid oxide fuel cell combined cooling, heating and power system in green buildings with hydrogen energy of byproduct water enables carbon neutrality transformation. However, underlying mechanisms on capacity sizing of combined cooling, heating and power system devices and its impacts on system techno-economy have not been figured out especially considering dynamic degradation and efficiency of associated devices. In this study, a multi-software optimization platform is established by MATLAB-TRNSYS co-simulation for sizing parametrical analysis, with well balance of modelling complexity and computational efficiency. A self-sufficient combined cooling, heating and power system is modelled integrating with a semi-empirical surrogate model of solid oxide fuel cell to interact with other balance of plant types efficiently. Total energy efficiency and annual total cost are optimized through parametrical analysis on device size of each component (battery, electrolyzer and solid oxide fuel cell) and analysis of variance for contribution ratio quantification. Results indicate that, the size increase in electrolyzer and solid oxide fuel cell will improve system total energy efficiency by 13.635 % and 2.194 %, but promote annual total cost by 4.042 × 10 4 $ and 2.389 × 10 3 $, respectively. Besides, sensitivity analysis indicates that the electrolyzer size prioritizes other design parameters in techno-economic performance. Optimal sizes of battery, electrolyzer and solid oxide fuel cell are in cell number range of 333 – 403, 17 – 20, and 26 – 30, respectively, with corresponding optimal total energy efficiency and annual total cost at 70.861 % – 72.147 % and 6.723 × 10 4 $ – 7.325 × 10 4 $, respectively. The research results can provide guidance on hydrogen-based cooling, heating and power system design and operation with techno-economic feasibility for low-carbon district energy transition.